Built an end-to-end e-commerce data analytics project to transform raw customer, product, transaction, campaign, and event data into actionable business insights.
Cleaned and processed datasets, performed exploratory data analysis, calculated key performance indicators, and developed visual reports to monitor sales and customer performance.
Tools: Python, Pandas, SQL, Excel, Power BI, Git/GitHub
Key areas: Data Cleaning • EDA • KPI Analysis • Dashboard Development • Business Insights

Analyzed a large HR attendance dataset using Microsoft Excel and Power Query to clean, transform, and summarize employee attendance data.
Built PivotTables, charts, and analytical summaries to identify attendance patterns and trends and present the findings in an easy-to-understand format.
Tools: Microsoft Excel • Power Query • PivotTables
Skills: Data Cleaning • Data Transformation • Data Analysis • Reporting • Data Visualization

Performed exploratory data analysis using Python to clean, transform, and investigate real-world datasets.
Used Pandas and NumPy for data preparation and analysis, identified trends and patterns, calculated key statistics, and created visualizations to communicate findings clearly.
Tools: Python • Pandas • NumPy • Matplotlib
Skills: Data Cleaning • EDA • Data Visualization • Statistical Analysis • Business Insights

Analyzed e-commerce sales and customer data using SQL to uncover business insights and key performance indicators.
Used SQL queries to clean and transform data, join multiple tables, calculate sales metrics, identify customer trends, and summarize business performance.
Skills: SQL • Data Cleaning • Joins • Aggregations • CTEs • KPI Analysis • Business Intelligence
Outcome: Created actionable insights that can help businesses understand sales performance, customer behavior, and product trends